Purpose: HALP score consisting of hemoglobin content, albumin content, lymphocyte count, and platelet count can comprehensively evaluate the inflammatory response and nutritional status. Many researchers have indicated that the HALP score is an effective predictor of the overall prognosis of various tumors. However, there is no relevant research to suggest whether the HALP score can predict the prognosis of patients with hepatocellular carcinoma (HCC). Patients and Methods: We retrospectively analyzed 273 HCC patients who underwent surgical resection. Hemoglobin content, albumin content, lymphocyte count, and platelet count in peripheral blood were measured for each patient. The relationship between the HALP score and overall survival (OS) was investigated. Results: With a mean of 56.69 ± 1.25 months follow-up, the 1-, 3-, and 5-year OS was 98.9%, 76.9%, and 55.3% for all patients, respectively. HALP scores (HR=1.708, 95% CI=1.192– 2.448, P=0.004) were significant independent risk factors of OS. The 1-, 3-, and 5-year OS were 99.3%, 84.3%, and 63.4% for patients with high HALP scores; and 98.6%, 69.8%, and 47.5% for patients with low HALP scores, respectively (P=0.018). In TNM I–II stage patients, compared with high HALP scores, low HALP scores have worse OS (P=0.039). In AFP positive patients, compared with high HALP scores, low HALP scores have worse OS (P=0.042). Conclusion: Our research showed the preoperative HALP score is an independent predictive factor of overall prognosis, and a low HALP score indicates a worse prognosis in HCC patients who underwent surgical resection.

The aim of this study was to analyze the risk factors, clinical features, and antimicrobial resistance of Pseudomonas putida (P putida) isolated from Tongji Hospital in Wuhan, China. The data of 44 patients with P putida infections were retrospectively reviewed in this study. All cases of P putida strains were detected by the clinical laboratory of Tongji Hospital in the period of January 2010 to December 2017. Antimicrobial susceptibility testing was conducted using Kirby-Bauer method. Forty-four effective strains of P putida were isolated, including 32 inpatients and 12 outpatients. The 32 inpatients cases were obtained from various departments, which were urosurgery wards (n = 5, 15.6%), pediatrics wards (n = 4, 12.5%), hepatic surgery wards (n = 4, 12.5%), among others. The isolates had been discovered from urine specimens (28.2%), blood specimens (21.9%), sputum specimens (12.5%), and so on. Twenty-five patients had histories of catheterization before the isolation of P putida. Twenty-four patients were in immunocompromised states, 5 patients had undergone surgery, catheterization and were taking immunosuppressive therapy simultaneously. Polymicrobial infections were found in some P putida cases, especially Stenotrophomonas maltophilia, Pseudomonas aeruginosa, and Escherichia coli. All the patients had treated by antimicrobial before culture. Multi-drug-resistant strains were detected in 75% of P putida isolates. The P putida strains were resistant to trimethoprim/sulfamethoxazole (97.7%), aztreonam (88.6%), minocyline (74.3%), ticarcillin/clavulanic acid (72.7%), and sensitive to amikacin (86.4%), imipenem (62.8%), gentamicin (56.8%). Catheterization or other invasive procedures, immunocompromised states, and underlying diseases increased the risks of P putida infections. Moreover, the P putida strains were highly resistant to trimethoprim/sulfamethoxazole, aztreonam, minocyline, ticarcillin/clavulanic acid.

(1) Background: The reasons for changes in the inflammatory markers of patients with surgically resected hepatocellular carcinoma are unclear. We aimed to investigate the association of an inflammatory status with the prognosis of patients with hepatocellular carcinoma, who underwent surgical resection. (2) Methods: We retrospectively enrolled 91 patients with Child A hepatocellular carcinoma, who had received surgical resection, to explore the influence of preoperative inflammatory markers and postoperative changes on the prognosis. (3) Results: The platelet-to-lymphocyte ratio (PLR) and its alteration were independent prognostic factors. Patients with a low PLR had a significantly better recurrence-free survival (RFS) than those with a high PLR (1-year RFS of 88.5% versus 50.0%; 3-year RFS of 62.1% versus 25.0%, p = 0.038). The patients with a low PLR showed a significantly better overall survival (OS) than those with a high PLR (1-year OS of 98.9% versus 75.0%; 3-year OS of 78.2% versus 25.0%, p = 0.005). The patients whose PLR had increased at 6 months after operation showed a worse OS than patients whose PLR had decreased (1-year OS of 96.3% versus 98.4%; 3-year OS of 63.0% versus 79.7%, p = 0.048). However, neither the neutrophil-to-lymphocyte ratio nor Onodera’s prognostic nutritional index had any prognostic significance. (4) Conclusions: The PLR and its alteration are significant prognostic factors for the RFS and OS of patients with Child A hepatocellular carcinoma who had received curative surgery.

Introduction: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in the world. The overall prognosis of patients with HCC is not very ideal. Early detection of HCC has become one of the important means to reduce mortality. More and more studies have pointed out that inflammatory markers based on hematology, such as Onodera’s prognostic nutritional index (OPNI), have important clinical significance. However, there is a lack of relevant research on the diagnosis of HCC by inflammatory markers. Methods: We retrospectively enrolled 633 patients and prospectively recruited 121 consecutive patients, to explore the correlation between inflammatory markers and diagnosis of HCC. Based on the prognostic indicators, different diagnostic models were constructed and the diagnostic performance of different models was further compared. Results: The best cutoff value of OPNI in the diagnosis of HCC is 43.925. Area under the receiver operating characteristics curve (AUC) of gender + age + AFP + OPNI diagnosis of HCC is 0.837 (95% CI: 0.702–0.868) in the retrospective cohort. Compared with gender + age + AFP, the Nagelkerke R2 of gender + age + AFP + OPNI increased from 0.234 to 0.426, and AUC increased by 0.0973 (95% CI: 0.0659–0.1290). DeLong test, net reclassification improvement (NRI) test, and integrated discrimination improvement (IDI) test are all statistically significant. In the prospective cohort, AUC of gender + age + AFP + OPNI diagnosis of HCC is 0.782 (95% CI: 0.696–0.869). Compared with gender + age + AFP, NRI test is statistically significant (categorical 0.0909 [95% CI: 0.0060–0.1759], p = 0.0359). Conclusion: In the process of monitoring the occurrence of HCC in patients with risk factors, OPNI can be included as appropriate to improve the accuracy of HCC diagnosis.

Previous studies mostly use single-type features to establish a prediction model. We aim to develop a comprehensive prediction model that effectively identify patients with poor prognosis for single hepatocellular carcinoma (HCC) based on artificial intelligence (AI). Patients and methods: 236 single HCC patients were studied to establish a comprehensive prediction model. We collected the basic information of patients and used AI to extract the features of magnetic resonance (MR) images. The clinical model based on linear regression (LR) algorithm (AUC: 0.658, 95%CI: 0.5021-0.8137), the radiomics model and deep transfer learning (DTL) model based on light gradient-boosting machine (Light GBM) algorithm (AUC: 0.761, 95%CI: 0.6326-0.8886 and AUC: 0.784, 95%CI: 0.6587-0.9087, respectively) were the optimal prediction models. A comparison revealed that the integrated nomogram had the largest area under the receiver operating characteristic curve (AUC) (all P < 0.05). In the training cohort, the integrated nomogram was predictive of recurrence-free survival (RFS) as well as overall survival (OS) (C-index: 0.735 and 0.712, P < 0.001). In the test cohort, the integrated nomogram also can predict RFS and OS (C-index: 0.718 and 0.740, P < 0.001) in patients. The integrated nomogram composed of signatures in the prediction models can not only predict the postoperative recurrence of single HCC patients but also stratify the risk of OS after the operation.